csch

Hyperbolic cosecant

Syntax

Y = csch(X)

Description

Y = csch(X) returns the hyperbolic cosecant of the elements of X. The csch function operates element-wise on arrays. The function accepts both real and complex inputs. All angles are in radians.

Examples

Hyperbolic Cosecant of Vector

Create a vector and calculate the hyperbolic cosecant of each value.

X = [0 pi 2*pi 3*pi];
Y = csch(X)

Y = 1×4

       Inf    0.0866    0.0037    0.0002

Graph of Hyperbolic Cosecant

Plot the hyperbolic cosecant over the domain $$-\pi <x<0$$ and $$0<x<\pi .$$

x1 = -pi+0.01:0.01:-0.01;
x2 = 0.01:0.01:pi-0.01;
y1 = csch(x1);
y2 = csch(x2);
plot(x1,y1,x2,y2)
grid on

Input Arguments

X — Input angles in radians

scalar | vector | matrix | multidimensional array

Input angles in radians, specified as a scalar, vector, matrix, or multidimensional array.

Data Types: single | double
Complex Number Support: Yes

More About

Hyperbolic Cosecant

The hyperbolic cosecant of x is equal to the inverse of the hyperbolic sine

$$\text{csch}\left(x\right)=\frac{1}{\sinh \left(x\right)}=\frac{2}{e^x-e^{-x}}.$$

In terms of the traditional cosecant function with a complex argument, the identity is

$$\text{csch}\left(x\right)=i\csc \left(ix\right).$$

Extended Capabilities

Tall Arrays

Calculate with arrays that have more rows than fit in memory.

This function fully supports tall arrays. For more information, see Tall Arrays.

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation
Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Thread-Based Environment

Run code in the background using MATLAB® backgroundPool or accelerate code with Parallel Computing Toolbox™ ThreadPool.

This function fully supports thread-based environments. For more information, see Run MATLAB Functions in Thread-Based Environment.

GPU Arrays

Accelerate code by running on a graphics processing unit (GPU) using Parallel Computing Toolbox™.

This function fully supports GPU arrays. For more information, see Run MATLAB Functions on a GPU (Parallel Computing Toolbox).

Distributed Arrays

Partition large arrays across the combined memory of your cluster using Parallel Computing Toolbox™.

This function fully supports distributed arrays. For more information, see Run MATLAB Functions with Distributed Arrays (Parallel Computing Toolbox).

Version History

Introduced before R2006a